Bring AI to Your Data

Get practical guidance for supporting AI agents with an open lakehouse, including the governance, isolation, and context needed for secure, auditable agentic workflows.

See how AI agents can drive unexpected data and compute costs — and what organizations can do to control the “agentic cost shift” and improve AI ROI.

See how open formats, interoperable metadata and flexible deployment can help enterprises adopt new analytics and AI tools without repeatedly moving data or rebuilding their architecture.

See why AI-ready data needs metadata, lineage, policy and business context that remain consistent across hybrid environments for both people and AI agents.

Compare leading data lakehouse providers and their capabilities for supporting governed data, hybrid environments, analytics, and AI workloads.

Get Gartner’s perspective on the evolving data lakehouse market, including key platform capabilities and considerations for evaluating solutions that support modern analytics workloads.

A guide to diagnosing and resolving Apache Iceberg issues in production lakehouse environments. Get troubleshooting strategies to improve the reliability and performance of Iceberg-based lakehouses.

72% of organizations say they need to significantly overhaul their AI architecture. This on-demand webinar series shows you how to get AI-ready data to power your AI.

Compare leading data fabric platforms and the capabilities they offer for integrating, governing, and accessing data across hybrid and multicloud environments.

Dive into this IDC Spotlight to see how data intelligence, governance, and unified data management can help turn distributed enterprise data into a trusted foundation for AI.

A practical roadmap for modernizing data lakes by migrating from Hive tables to Apache Iceberg. Learn how to reduce data copies, improve interoperability, and create a more flexible foundation for analytics and AI.